| other,5-1-P01-1007,bq | theoretical study of the <term> range concatenation | grammar | [ RCG ] formalism </term> has revealed many | #1604 The theoretical study of the range concatenation grammar [RCG] formalism has revealed many attractive properties which may be used in NLP. |
| lr,11-3-P01-1007,bq | <term> RCG </term> , any <term> tree adjoining | grammar | </term> can be parsed in <term> O ( n6 ) time | #1668 For example, after translation into an equivalent RCG, any tree adjoining grammar can be parsed in O(n6) time. |
| model,11-6-P01-1007,bq | method </term> on a <term> wide coverage English | grammar | </term> are given . While <term> paraphrasing | #1749 The results of a practical evaluation of this method on a wide coverage English grammar are given. |
| other,9-2-P01-1047,bq | leads to a neat relation to <term> categorial | grammar | </term> , ( yielding a treatment of <term> | #1956 Our logical definition leads to a neat relation to categorial grammar, (yielding a treatment of Montague semantics), a parsing-as-deduction in a resource sensitive logic, and a learning algorithm from structured data (based on a typing-algorithm and type-unification). |
| other,15-2-P05-1067,bq | probabilistic synchronous dependency insertion | grammar | </term> . <term> Synchronous dependency insertion | #9443 In this paper, we present a syntax-based statistical machine translation system based on a probabilistic synchronous dependency insertion grammar. |
| other,9-4-P05-1067,bq | <term> approach </term> to inducing such a <term> | grammar | </term> from <term> parallel corpora </term> | #9469 We first introduce our approach to inducing such agrammar from parallel corpora. |
| other,12-3-P06-1018,bq | powerful enough to strongly simulate many <term> | grammar | formalisms </term> , such as <term> rewriting | #11101 This formalism is both elementary and powerful enough to strongly simulate manygrammar formalisms, such as rewriting systems, dependency grammars, TAG, HPSG and LFG. |
| tech,22-1-P06-2001,bq | checker </term> to be integrated in a <term> | grammar | checker </term> for <term> Basque </term> . After | #11222 In this paper, we describe the research using machine learning techniques to build a comma checker to be integrated in agrammar checker for Basque. |
| other,5-4-J82-3002,bq | </term> . With the aid of a <term> logic-based | grammar | formalism </term> called <term> extraposition | #12892 With the aid of a logic-based grammar formalism called extraposition grammars, Chat-80 translates English questions into the Prolog subset of logic. |
| other,1-3-P84-1047,bq | are grouped together . Like <term> semantic | grammar | </term> , this allows easy exploitation of | #13352 Like semantic grammar, this allows easy exploitation of limited domain semantics. |
| other,0-1-P86-1038,bq | formalisms </term> . <term> Unification-based | grammar | formalisms </term> use structures containing | #14624 Unification-based grammar formalisms use structures containing sets of features to describe linguistic objects. |
| tech,4-1-C90-1013,bq | article introduces a <term> bidirectional | grammar | generation system </term> called <term> feature | #16215 This article introduces a bidirectional grammar generation system called feature structure-directed generation, developed for a dialogue translation system. |
| other,1-4-C90-1013,bq | the <term> derivation tree </term> . The <term> | grammar | </term> for this <term> generator </term> is | #16266 Thegrammar for this generator is designed to properly generate the speaker's intention in a telephone dialogue. |
| other,14-1-C90-3014,bq | system </term> using the <term> unification-based | grammar | formalism </term> : <term> Korean Phonology | #16370 This paper describes the framework of a Korean phonological knowledge base system using the unification-based grammar formalism: Korean Phonology Structure Grammar (KPSG). |
| other,2-3-H90-1016,bq | sentence hypotheses </term> . To avoid <term> | grammar | coverage problems </term> we use a <term> fully-connected | #16905 To avoidgrammar coverage problems we use a fully-connected first-order statistical class grammar. |
| other,8-3-H90-1016,bq | fully-connected first-order statistical class | grammar | </term> . The <term> speech-search algorithm | #16915 To avoid grammar coverage problems we use a fully-connected first-order statistical class grammar. |
| lr,20-4-H90-1060,bq | word error rate </term> on a standard <term> | grammar | </term> and <term> test set </term> from the <term> | #17090 With only 12 training speakers for SI recognition, we achieved a 7.5% word error rate on a standardgrammar and test set from the DARPA Resource Management corpus. |
| tech,8-1-C92-2068,bq | expensive part of <term> unification-based | grammar | parsing </term> . We focus on one speed-up | #17955 Graph unification remains the most expensive part of unification-based grammar parsing. |
| other,10-4-H92-1026,bq | contrast to the usual approach of further <term> | grammar | </term> tailoring via the usual <term> linguistic | #18991 This stands in contrast to the usual approach of furthergrammar tailoring via the usual linguistic introspection in the hope of generating the correct parse. |
| lr,28-5-H92-1060,bq | sentences </term> were not covered by the <term> | grammar | </term> . We also report here on the performance | #19496 It was clear that the robust parser allowed us to answer many more questions correctly, as over a third of the sentences were not covered by thegrammar. |
